The development of modern portfolio theory led to a sea change in the way that investment managers and investors viewed a portfolio of investments. Intelligent decisions were being made about how much of each asset class should be allocated to provide the greatest expected return for the lowest level of risk. The result was a major leap forward in the understanding of investments and a new approach to building portfolios.
Underlying modern portfolio theory, however, were a number of significant assumptions: (1) that asset returns were comparably measured; (2) that levels of liquidity were roughly the same across asset classes; (3) that long histories of performance in these asset classes had been reliably observed; and (4) that both the types and characteristics of risk in these asset classes were similar and well-understood.
These assumptions have served well in the traditional investment world, because they are reasonable approximations of reality for stocks, bonds, and cash. But the financial world is a dynamic one, constantly presenting investors with both new opportunities and challenges. This dynamism has led to a raft of non-traditional or alternative investment products—including hedge funds and illiquid investments such as private equity and real estate vehicles—which investors can access to improve the performance of their portfolios.
The emergence of these new asset classes as an increasingly significant part of many high-net-worth investors' portfolios has also created potential problems. The assumptions that were reasonable for the traditional asset classes are often violated by alternative ones, which can be less liquid, widely disparate in their characteristics and may have poor or inconsistently-recorded historical performance data. The result is that investors are left in a quandary of whether they should take advantage of these investments even though they might not understand them very well. Resolving these questions requires the development of new techniques and tools.
It is difficult to pin down the value of private equity, real estate and other illiquid investments. An innovative holistic system is needed for investors to make intelligent decisions about balancing liquidity needs and the potential for higher returns.
In many investors' quest to moderate risk and increase their portfolios' returns (i.e., the real reasons to diversify), they may have added assets that could throw a portfolio out of balance. The Institute for Private Investors, an educational organization for investors with a minimum of $10 million in investable assets, reports that its average member now has 18% of assets in alternative investments, such as real estate and private equity. In a recent IPI survey, more than 30% of these families said they planned to increase their holdings in real estate and private equity. That trend poses two related problems.
The first is that real estate holdings, credit structures (which purchase bond portfolios and seek to increase yields by borrowing against the assets to buy more securities) and investments in venture capital, leveraged buyouts, and other styles of private equity are illiquid. They typically must be held for years, and because they cannot be bought or sold on demand, it is difficult to determine their exact valuation at any given moment.
That leads to a second problem. It is extremely difficult to include illiquid investments in asset allocation plans. Traditional methods of optimizing a portfolio to fit investors' goals and risk tolerance, which have proven useful in determining percentages of stocks, bonds and cash and in a portfolio, are virtually powerless to handle the very different attributes of illiquid assets.
Treating liquid and illiquid assets as if they were parts of separate portfolios does nothing to answer the question of how much real estate or private equity a particular investor should hold in total. At the same time, sidestepping the liquidity issue and lumping together traditional assets with real estate and private equity ignores basic differences between these two types of holdings. The resulting portfolio can have much more risk than an investor wants.
To appreciate the challenges that need to be addressed, the long-established method for building a portfolio should be considered. In the traditional approach, an advisor helps determine an investor's long-term goals and risk tolerance, and then considers the returns and risks that stocks and bonds have historically produced. Stocks have historically returned 10.2% annually while sometimes suffering sizable losses. Bonds have produced about half the returns of stocks but with much lower risks. Factoring in all the data, the advisor then seeks to create an optimal portfolio with a mix of assets that attempts to provide maximum returns with acceptable levels of risk.
This is an oversimplified description of a process that depends on sophisticated analyses of asset choices as well as on an advisor's judgment and experience. Still, the methodology of traditional asset allocation is well established. However, when illiquid investments are added to the mix, that problem becomes vexing.
Viewed according to the traditional technique of asset allocation, private equity and real estate seem to deserve a heavy weighting in nearly every portfolio. Venture capital investments, for example, have returned almost 17% annually in the past 20 years, according to Thomson Venture Economics. That is eight percentage points better than the returns achieved by stocks on NASDAQ. And based on some historical measures, venture capital is also less risky, at least in terms of volatility, a measure of how much returns move up and down.
On the basis of those raw numbers, an investor might decide an optimum portfolio would hold most of its assets in venture capital. But there are several reasons why that approach should be tempered. For one, venture funds are more volatile than the data suggest, because of the very different ways stocks and venture capital funds are priced. Stock prices change constantly, and calculations of equities' volatility are based on those minute-to-minute fluctuations. In addition, when markets close, any stock has a measurable value. In contrast, the managers of venture capital funds seldom publish performance data more than once a quarter. Moreover, even that data may represent little more than rough guesses. Because there are no public markets for these investments, venture fund managers must estimate the value of their holdings. The true value of a fund may not be known until the companies in a fund's portfolio have all been sold—perhaps a decade after investors put up their money.
As a result, although venture capital appears to be less volatile than stocks, this is only because those infrequent and imprecise valuations tend to smooth out the rough patches, suggesting that prices are gradually moving higher when, in fact, the value of holdings bounces up and down.
Investment advisors make a recommendation of a mix of assets, e.g., stocks, bonds, cash, that they believe will perform best based on clients' objectives and risk tolerance. Historically, there have been quantitative models which seek to mathematically optimize a portfolio by looking at historical returns among all the different asset classes and then computing the right balance of all those different asset classes based upon the clients' risk tolerance and objectives regarding their portfolio.
There are also qualitative approaches whereby investment advisors will not necessarily undertake significant computational analysis on how a given asset class will perform, but will essentially use their intuition and the economic outlook for a given asset class. The quantitative model, however, is generally considered as the primary basis for making responsible asset allocation recommendations.
As noted above, an issue with the quantitative model is that the ability to make recommendations is typically limited to traditional asset classes, e.g., stocks, bonds and cash. (Hedge funds may sometimes be included, but these are a very gray area). These traditional asset classes generally have a lot of history and good data available, with the exception of hedge funds. It is possible to fairly easily run mathematical models for the past 30 or so years and to be able to make some fairly defensible recommendations about what those asset classes will do and thereby allowing the advisor to construct portfolios that have a relatively high probability of satisfying the investors' objectives.
This quantitative model, however, has been limited to traditional asset classes. High net worth private clients indeed have access to many more products, e.g., alternative investment products and vehicles, not just the traditional asset classes of stocks, bonds, and cash. They have access to hedge funds, private equity, real estate, etc., which are investment classes that are not considered traditional and are not necessarily liquid, which is one of the big criteria of traditional asset classes.
There has not been a model to intelligently and systematically allocate among this larger set of asset classes and between traditional and alternative investments. Therefore, as an example, it is very hard to determine how much private equity, an illiquid asset class, should be held relative to the amount of public equity, a very liquid asset class. There is not a consolidated, single model to do any kind of rigorous optimization among all these asset classes. The models have been limited to just the traditional, or liquid, component of a portfolio.
Accordingly, there is a need for a methodology by which an investment advisor can intelligently recommend a mix of assets to best meet a high net worth investor's objectives and that is consistent with the investor's risk tolerance. More particularly, high net worth individual investors, who are clients at private banks, should intelligently consider untraditional or alternative asset classes—these can be very beneficial to such clients' portfolios.